Whisper small by ehzawad
This model is a fine-tuned version of openai/whisper-small on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1104
- Wer: 31.3274
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2424 | 0.27 | 500 | 0.2407 | 63.1783 |
| 0.1559 | 0.53 | 1000 | 0.1633 | 48.0380 |
| 0.1255 | 0.8 | 1500 | 0.1394 | 42.6625 |
| 0.0899 | 1.07 | 2000 | 0.1231 | 38.6982 |
| 0.0872 | 1.34 | 2500 | 0.1172 | 37.3415 |
| 0.0755 | 1.6 | 3000 | 0.1091 | 35.4971 |
| 0.0786 | 1.87 | 3500 | 0.1042 | 34.6567 |
| 0.0499 | 2.14 | 4000 | 0.1047 | 33.2752 |
| 0.0468 | 2.4 | 4500 | 0.1027 | 32.7874 |
| 0.0436 | 2.67 | 5000 | 0.1019 | 32.2877 |
| 0.0379 | 2.94 | 5500 | 0.1000 | 31.7168 |
| 0.025 | 3.2 | 6000 | 0.1062 | 31.6455 |
| 0.0282 | 3.47 | 6500 | 0.1050 | 31.4699 |
| 0.0249 | 3.74 | 7000 | 0.1060 | 31.3737 |
| 0.0231 | 4.01 | 7500 | 0.1049 | 31.1969 |
| 0.0183 | 4.27 | 8000 | 0.1104 | 31.3274 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
